Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes. - Stephan Eismann; Raphael J. L. Townshend; Nathaniel Thomas; Milind Jagota; Bowen Jing 002; Ron O. Dror (CoRR, 2020)

Protein model quality assessment using rotation-equivariant, hierarchical neural networks. - Stephan Eismann; Patricia Suriana; Bowen Jing 002; Raphael J. L. Townshend; Ron O. Dror (CoRR, 2020)

Learning from Protein Structure with Geometric Vector Perceptrons. - Bowen Jing 002; Stephan Eismann; Patricia Suriana; Raphael John Lamarre Townshend; Ron O. Dror (ICLR, 2021)

ATOM3D: Tasks on Molecules in Three Dimensions. - Raphael J. L. Townshend; Martin Vögele; Patricia Suriana; Alexander Derry; Alexander S. Powers; Yianni Laloudakis; Sidhika Balachandar; Bowen Jing 002; Brandon M. Anderson; Stephan Eismann; Risi Kondor; Russ B. Altman; et al. (NeurIPS Datasets and Benchmarks, 2021)

Equivariant Graph Neural Networks for 3D Macromolecular Structure. - Bowen Jing 002; Stephan Eismann; Pratham N. Soni; Ron O. Dror (CoRR, 2021)

Subspace Diffusion Generative Models. - Bowen Jing 002; Gabriele Corso; Renato Berlinghieri; Tommi S. Jaakkola (ECCV (23), 2022)

Torsional Diffusion for Molecular Conformer Generation. - Bowen Jing 002; Gabriele Corso; Jeffrey Chang; Regina Barzilay; Tommi S. Jaakkola (NeurIPS, 2022)

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. - Gabriele Corso; Hannes Stärk; Bowen Jing 002; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2023)

EigenFold: Generative Protein Structure Prediction with Diffusion Models. - Bowen Jing 002; Ezra Erives; Peter Pao-Huang; Gabriele Corso; Bonnie Berger; Tommi S. Jaakkola (CoRR, 2023)

Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design. - Hannes Stärk; Bowen Jing 002; Regina Barzilay; Tommi S. Jaakkola (CoRR, 2023)

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. - Bowen Jing 002; Tommi S. Jaakkola; Bonnie Berger (ICLR, 2024)

AlphaFold Meets Flow Matching for Generating Protein Ensembles. - Bowen Jing 002; Bonnie Berger; Tommi S. Jaakkola (ICML, 2024)

Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design. - Hannes Stärk; Bowen Jing 002; Regina Barzilay; Tommi S. Jaakkola (ICML, 2024)

Dirichlet Flow Matching with Applications to DNA Sequence Design. - Hannes Stärk; Bowen Jing 002; Chenyu Wang 003; Gabriele Corso; Bonnie Berger; Regina Barzilay; Tommi S. Jaakkola (ICML, 2024)

Generative Modeling of Molecular Dynamics Trajectories. - Bowen Jing 002; Hannes Stärk; Tommi S. Jaakkola; Bonnie Berger (NeurIPS, 2024)

Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models. - Ezra Erives; Bowen Jing 002; Tommi S. Jaakkola (CoRR, 2024)

ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids. - Hannes Stärk; Bowen Jing 002; Tomas Geffner; Jason Yim; Tommi S. Jaakkola; Arash Vahdat; Karsten Kreis (ICLR, 2025)

Continuously Tempered Diffusion Samplers. - Ezra Erives; Bowen Jing 002; Peter Holderrieth; Tommi S. Jaakkola (CoRR, 2025)

Learning residue level protein dynamics with multiscale Gaussians. - Mihir Bafna; Bowen Jing 002; Bonnie Berger (CoRR, 2025)

AI-based Methods for Simulating, Sampling, and Predicting Protein Ensembles. - Bowen Jing 002; Bonnie Berger; Tommi S. Jaakkola (CoRR, 2025)